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    • Patrick von Platen's avatar
      [Docs] Correct links (#432) · 44968e42
      Patrick von Platen authored
      44968e42
    • anton-l's avatar
      Release: 0.3.0 · 3f55d135
      anton-l authored
      3f55d135
    • Satpal Singh Rathore's avatar
      Improve unconditional diffusers example (#414) · 1d7adf13
      Satpal Singh Rathore authored
      
      
      * use gpu and improve
      
      * Update README.md
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * Update README.md
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      1d7adf13
    • Satpal Singh Rathore's avatar
      Improve latent diff example (#413) · f4a785ce
      Satpal Singh Rathore authored
      
      
      * improve latent diff example
      
      * use gpu
      
      * Update README.md
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * Update README.md
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      f4a785ce
    • Pedro Cuenca's avatar
      Inference support for `mps` device (#355) · 5dda1735
      Pedro Cuenca authored
      * Initial support for mps in Stable Diffusion pipeline.
      
      * Initial "warmup" implementation when using mps.
      
      * Make some deterministic tests pass with mps.
      
      * Disable training tests when using mps.
      
      * SD: generate latents in CPU then move to device.
      
      This is especially important when using the mps device, because
      generators are not supported there. See for example
      https://github.com/pytorch/pytorch/issues/84288.
      
      In addition, the other pipelines seem to use the same approach: generate
      the random samples then move to the appropriate device.
      
      After this change, generating an image in MPS produces the same result
      as when using the CPU, if the same seed is used.
      
      * Remove prints.
      
      * Pass AutoencoderKL test_output_pretrained with mps.
      
      Sampling from `posterior` must be done in CPU.
      
      * Style
      
      * Do not use torch.long for log op in mps device.
      
      * Perform incompatible padding ops in CPU.
      
      UNet tests now pass.
      See https://github.com/pytorch/pytorch/issues/84535
      
      
      
      * Style: fix import order.
      
      * Remove unused symbols.
      
      * Remove MPSWarmupMixin, do not apply automatically.
      
      We do apply warmup in the tests, but not during normal use.
      This adopts some PR suggestions by @patrickvonplaten.
      
      * Add comment for mps fallback to CPU step.
      
      * Add README_mps.md for mps installation and use.
      
      * Apply `black` to modified files.
      
      * Restrict README_mps to SD, show measures in table.
      
      * Make PNDM indexing compatible with mps.
      
      Addresses #239.
      
      * Do not use float64 when using LDMScheduler.
      
      Fixes #358.
      
      * Fix typo identified by @patil-suraj
      Co-authored-by: default avatarSuraj Patil <surajp815@gmail.com>
      
      * Adapt example to new output style.
      
      * Restore 1:1 results reproducibility with CompVis.
      
      However, mps latents need to be generated in CPU because generators
      don't work in the mps device.
      
      * Move PyTorch nightly to requirements.
      
      * Adapt `test_scheduler_outputs_equivalence` ton MPS.
      
      * mps: skip training tests instead of ignoring silently.
      
      * Make VQModel tests pass on mps.
      
      * mps ddim tests: warmup, increase tolerance.
      
      * ScoreSdeVeScheduler indexing made mps compatible.
      
      * Make ldm pipeline tests pass using warmup.
      
      * Style
      
      * Simplify casting as suggested in PR.
      
      * Add Known Issues to readme.
      
      * `isort` import order.
      
      * Remove _mps_warmup helpers from ModelMixin.
      
      And just make changes to the tests.
      
      * Skip tests using unittest decorator for consistency.
      
      * Remove temporary var.
      
      * Remove spurious blank space.
      
      * Remove unused symbol.
      
      * Remove README_mps.
      Co-authored-by: default avatarSuraj Patil <surajp815@gmail.com>
      Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> 
      5dda1735
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